Storage stability of injection-molded starch-zein plastics under dry and humid conditions

Corn starch and zein mixtures (4 : 1 dry weight) were extruded and injection-molded in the presence of plasticizers (glycerol and water). Tensile strength and percentage elongation of the molded plastics were measured before and after 1 week of storage under a dry or humid condition (11 or 93% RH). With 10–12% glycerol and 6–8% water, injection-molded plastics had relatively good tensile properties (20- to 25-MPa tensile strength and 3.5–4.7% elongation). But while exposed to dry conditions (11% RH), the molded plastics lost weight (0.5–1.5% in 7 days) and became very brittle, with significant decreases in tensile strength and elongation. Partial replacement (5–10%) of starch with a maltodextrin (average DE 5) reduced the glass transition and melting temperatures of the starch-zein mixture as well as the dry storage stability. Using potato starch instead of corn starch significantly improved the dry storage stability of the injection-molded starch-zein plastics (18- vs 11-MPa tensile strength). Anionic corn starches with a maleate or succinate group (DS<0.01) produced injection-molded plastics with improved tensile properties and storage stability. Plastics prepared from the starch maleate and zein mixture retained the strength during 1 week of dry storage without a significant change (26-MPa tensile strength and 3.7% elongation after 1 week of storage).Paper presented at the Bio/Environmentally Degradable Polymer Society—Second National Meeting, August 19–21, 1993, Chicago, Illinois.Journal paper No. J-15561 of the Iowa Agriculture and Home Economics Experiment Station, Ames, Iowa, Project No. 2863.     

EFFECTS OF INITIAL ABSTRACTION AND URBANIZATION ON ESTIMATED RUNOFF USING CN TECHNOLOGY1

ABSTRACT: Few studies have been conducted to explore the effects of initial abstraction on estimated direct runoff despite the widespread use of the curve number (CN) method in many hydrologic models to estimate direct runoff. In this study, use of a 5 percent ratio of initial abstraction (I_a) to storage (S) to estimate daily direct runoff with modified CN values for a 5 percent I_a/S value was investigated using the Long‐Term Hydrologic Impact Assessment (L‐THIA) geographic information system (GIS). In addition, the effects on estimated runoff of altering the hydrologic soil group due to urbanization were investigated. The L‐THIA model was applied to the Indiana Little Eagle Creek watershed with 5 percent and 20 percent I_a/S values, considering hydrologic soil group alteration due to urbanization. The results indicate that uses of a 5 percent l_a/S and modified CN values and Hydrologic Soil Group D for urbanized areas in model runs can improve long term direct runoff prediction.     

A dynamic compartment model for assessing the transfer of radionuclide deposited onto flooded rice-fields

A dynamic compartment model has been studied to estimate the transfer of radionuclides deposited onto flooded rice-fields after an accidental release. In the model, a surface water compartment and a direct shoot-base absorption from the surface water to the rice-plant, which are major features discriminating the present model from the existing model, has been introduced to account for the flooded condition of rice-fields. The model has been applied to the deposition experiments of 137Cs on rice-fields that were performed at three different times to simulate the deposition before transplanting (May 2) and during the growth of the rice (June 1 and August 12), respectively. In the case of the deposition of May 2, the root-uptake is the most predominant process for transferring 137Cs to the rice-body and grain. When the radionuclide is applied just after transplanting (June 1), the activity of the body is controlled by the shoot-base absorption and the activity of the grain by the root-uptake. The deposition just before ear-emergence (August 12) shows that the shoot-base absorption contributes entirely to the increase of both the activities of the body and grain. The model prediction agrees within one or two factors with the experimental results obtained for a respective deposition experiment.     

Odor and gas release from anaerobic treatment lagoons for swine manure

Odor and gas release from anaerobic lagoons for treating swine waste affect air quality in neighboring communities but rates of release are not well documented. A buoyant convective flux chamber (BCFC) was used to determine the effect of lagoon loading rate on measured odor and gas releases from two primary lagoons at a simulated wind speed of 1.0 m s(-1). Concentrations of ammonia (NH3), hydrogen sulfide (H2S), carbon dioxide (CO2), sulfur dioxide (SO2), and nitric oxide (NO) in 50-L air samples were measured. A panel of human subjects, whose sensitivity was verified with a certified reference odorant, evaluated odor concentration, intensity, and hedonic tone. Geometric mean odor concentrations of BCFC inlet and outlet samples and of downwind berm samples were 168 +/- 44 (mean +/- 95% confidence interval), 262 +/- 60, and 114 +/- 38 OU(E) m(-3) (OU(E), European odor unit, equivalent to 123 microg n-butanol), respectively. The overall geometric mean odor release was 2.3 +/- 1.5 OU(E) s(-1) m(-2) (1.5 +/- 0.9 OU s(-1) m(-2)). The live mass specific geometric mean odor release was 13.5 OU(E) s(-1) AU(-1) (animal unit = 500 kg live body mass). Overall mean NH3, H2S, CO2 and SO2 releases were 101 +/- 24, 5.7 +/- 2.0, 852 +/- 307, and 0.5 +/- 0.4 microg s(-1) m(-2), respectively. Nitric oxide was not detected. Odor concentrations were directly proportional to H2S and CO2 concentrations and odor intensity, and inversely proportional to hedonic tone and SO2 concentration (P < 0.05). Releases of NH3, H2S, and CO2 were directly proportional (P < 0.05) to volatile solids loading rate (VSLR).     

Improvement of thermal hydrolysis rate of dichloroacetic acid using alcohol

Dichloroacetic acid (DCAA) is produced during the oxidation of trichloroethylene. It is also produced in drinking water treatment as a disinfection by-product. DCAA is a problem material, because of its toxicity. The objective of this research is to find the final products and the reaction pathway of the DCAA decomposition by hydrolysis, and to increase the hydrolysis rate. The removal of both chlorine atoms in DCAA structure was achieved with hydrolysis at around 75 degrees C, and the final products were oxalic acid and glycolic acid. The reaction pathway was the production of oxalic acid and glycolic acid from two glyoxylic acid molecules by Cannizzaro reaction after the glyoxylic acid production from dechlorination of DCAA with hydrolysis. The hydrolysis rate of DCAA was increased with the use of 90% ethanol solution as solvent. The activation energy of DCAA was about 80 kJ/mol in it, while it was around 105 kJ/mol in water.     

Prediction of effluent concentration in a wastewater treatment plant using machine learning models

Of growing amount of food waste, the integrated food waste and waste water treatment was regarded as one of the efficient modeling method. However, the load of food waste to the conventional waste treatment process might lead to the high concentration of total nitrogen(T-N) impact on the effluent water quality. The objective of this study is to establish two machine learning models—artificial neural networks(ANNs) and support vector machines(SVMs), in order to predict 1-day interval T-N concentration of effluent from a wastewater treatment plant in Ulsan, Korea. Daily water quality data and meteorological data were used and the performance of both models was evaluated in terms of the coefficient of determination(R~2), Nash–Sutcliff efficiency(NSE), relative efficiency criteria(d rel). Additionally, Latin-Hypercube one-factor-at-a-time(LH-OAT) and a pattern search algorithm were applied to sensitivity analysis and model parameter optimization, respectively. Results showed that both models could be effectively applied to the 1-day interval prediction of T-N concentration of effluent. SVM model showed a higher prediction accuracy in the training stage and similar result in the validation stage.However, the sensitivity analysis demonstrated that the ANN model was a superior model for 1-day interval T-N concentration prediction in terms of the cause-and-effect relationship between T-N concentration and modeling input values to integrated food waste and waste water treatment. This study suggested the efficient and robust nonlinear time-series modeling method for an early prediction of the water quality of integrated food waste and waste water treatment process.     

MINIMIZING THE IMPACT OF URBANIZATION ON LONG TERM RUNOFF1

Increasing concern about the problems caused by urban sprawl has encouraged development and implementation of smart growth approaches to land use management. One of the goals of smart growth is water resources protection, in particular minimizing the runoff impact of urbanization. To investigate the magnitude of the potential benefits of land use planning for water resources protection, possible runoff impacts of historical and projected urbanization were estimated for two watersheds in Indiana and Michigan using a long term hydrological impact analysis model. An optimization component allowed selection of land use change placements that minimize runoff increase. Optimizing land use change placement would have reduced runoff increase by as much as 4.9 percent from 1973 to 1997 in the Indiana study watershed. For nonsprawl and sprawl scenarios in the Michigan watershed for 1978 to 2040, optimizing land use change placement would have reduced runoff increase by 12.3 percent and 20.5 percent, respectively. The work presented here illustrates both an approach to assessing the magnitude of the impact of smart growth and the significant potential scale of smart growth in moderating runoff changes that result from urbanization. The results of this study have significant implications for urban planning.     

Process evaluation for optimization of EDTA use and recovery for heavy metal removal from a contaminated soil

This study aimed to establish an optimized, closed loop application of ethylenediaminetetraacetic acid (EDTA) in heavy metal removals from a contaminated soil through integrating EDTA recovery/regeneration and metal precipitation processes in the treatment train. Three divalent heavy metals were investigated, namely, Pb, Cd, and Ni. The extractability of the metals by EDTA followed the decreasing order of CdPb>Ni. The first part of this study was to search for the optimal use of the fresh EDTA in removing these heavy metals from the contaminated soil. The second part of this study was devoted to the recovery/regeneration of the spent EDTA which followed the sequential processes involving (1) complex destabilization by adding ferric ion (Fe(III)) to liberate Pb, Cd, and Ni, (2) precipitation of the liberated Pb, Cd, and Ni in phosphate (PO4(3-)) forms, and (3) precipitation of the excess Fe(III) which eventually produced free EDTA for reuse. The process variables were dosages of Fe(III) and PO4(3-), pH and reaction times. Laborious trial experiments would be needed in searching for the optimum conditions for the above processes. To expedite this exercise, a geochemical equilibrium model, MINTEQA2, was used to find the thermodynamically favorable conditions for recoveries of both EDTA and heavy metals. This was then followed by experimental examination of the process kinetics to observe for the optimal reaction time for each thermodynamically favorable process. This study revealed that 2 h of reaction time each for the complex destabilization reaction and the metal phosphate precipitation reaction was sufficient to achieve equilibrium. With the optimized process condition identified in this study, a total of 95%, 89% and 90% of the extracted Pb, Cd and Ni, respectively, could be precipitated from the spent EDTA solution, with 84% EDTA recovery. The reused EDTA maintained more than 90% of its preceding extraction power in each cycle of reuse.